Computer vision (anguoyang)

anguoyang

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Location:Tokyo

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Computer vision's repositories

FixRes

This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423

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snorkel

A system for quickly generating training data with weak supervision

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jetson-inference

Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

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simrdwn

Rapid satellite imagery object detection

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CMUComputationalPhotography

Jupyter Notebooks for CMU Computational Photography Course 15.463

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ssd_detectors

SSD-based object and text detection with Keras, SSD, DSOD, TextBoxes, SegLink, TextBoxes++, CRNN

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Deep-Learning-Approach-for-Surface-Defect-Detection

(最先进的缺陷检测网络) A Tensorflow implementation of "Segmentation-Based Deep-Learning Approach for Surface-Defect Detection"

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Lightweight-Segmentation

Lightweight models for real-time semantic segmentation(include mobilenetv1-v3, shufflenetv1-v2, igcv3, efficientnet).

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Retinaface

Retinaface windows

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deep-face-alignment

The MXNet Implementation of Stacked Hourglass and Stacked SAT for Robust 2D and 3D Face Alignment

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SENet

Squeeze-and-Excitation Networks

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High-Performance-Face-Recognition

🔥🔥Several High-Performance Models for Unconstrained/Large-Scale/Low-Shot Face Recognition🔥🔥

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pytorch-inference

PyTorch 1.0 inference in C++ on Windows10 platforms

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MC-GAN

Multi-Content GAN for Few-Shot Font Style Transfer at CVPR 2018

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paper-reading

Notes about papers I read (in Japanese)

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awesome-xamarin-forms

A curated list of awesome Xamarin.Forms libraries and resources

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Face-Pose-Net

Estimate 3D face pose (6DoF) or 11 parameters of 3x4 projection matrix by a Convolutional Neural Network

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awesome-ai-infrastructures

Infrastructures™ for Machine Learning Training/Inference in Production.

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Deep-Learning-in-Production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

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deepstream-plugins

Samples for TensorRT/Deepstream for Tesla & Jetson

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dl-inference-server

Deep Learning Inference Server Clients

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machinelearning-1

ML.NET is an open source and cross-platform machine learning framework for .NET.

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awesome-Face_Recognition

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

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EasyAI

AI platform for everyone

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DeepLearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,近30万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06

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mobileFacenet-ncnn

implementation of nccnn's mobileFacenet

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DeepSpeech

A TensorFlow implementation of Baidu's DeepSpeech architecture

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MVision

机器人视觉 无人驾驶 视觉SLAM ORB LSD SVO DSO 深度学习目标检测yolov3 行为检测 opencv PCL 双目视觉

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awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

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